A temporal object relational SQL language with attribute timestamping in a temporal transparency environment

Chau, Vo Thi Ngoc; Chittayasothorn, Suphamit

doi:10.1016/j.datak.2008.06.008

Cited by 13 publications

(8 citation statements)

References 27 publications

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“…There are very few (Chau and Chittayasothorn 2008;and Snodgrass 2010) commercial databases yet on the market, perhaps due to the complex nature of temporal data. This article presents a technical outline of how to use the conventional commercial databases to update with temporal data.…”

Section: Temporal Data Update Methodologiesmentioning

confidence: 99%

“…Current commercial database systems provide little built-in capabilities to capture transaction lineage or to support query language for temporal data management (Mahmood et al 2010). As of today, a few companies started providing time-referenced data storing functionality and SQL facilities in their DBMS system (Chau and Chittayasothorn 2008;and Snodgrass 2010). In data warehouses, data comes from many sources and data warehouse refreshes happen several times a day.…”

Section: Literature Reviewmentioning

confidence: 99%

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Temporal Data Update Methodologies for Data Warehousing

Rahman¹

2014

Journal of the Southern Association for Information Systems

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Data warehouse applications and business intelligence (BI) communities have been increasingly feeling the need to collect temporal data for accountability and traceability reasons. This necessitates building capabilities to capture and view transaction lineage in data warehouses based on timestamps. Data as of a point in time can be obtained across multiple tables or multiple subject areas, resolving consistency and synchronization issues. In this article we discuss implementations such as temporal data update methodologies, coexistence of load and query against the same table, performance of load and report queries, and maintenance of views on top of the tables with temporal data. We show how to pull data from heterogeneous sources and how to perform join operations with inequality predicates with more than one source table and then load them in analytical subject area tables maintaining transaction lineage. We propose several business views based on timestamp filters for use by different applications.

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Section: Temporal Data Update Methodologiesmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Temporal Data Update Methodologies for Data Warehousing

Rahman¹

2014

Journal of the Southern Association for Information Systems

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“…However, little Object-Relational temporal extensions have been proposed [23,24,25]. In [23] the authors propose a valid-time extension of SQL, based on the model proposed in [11], and its implementation on an Object-Relational DBMS.…”

Section: Related Workmentioning

confidence: 99%

“…In [24], the algebra of a generalized temporal database model supporting temporal relations nested to any finite depth is presented; this model deal with the valid-time dimension and the author does not yet, to our knowledge, defines an extension of SQL to support the temporal nested features. The temporal language proposed in [25] integrates only the valid-time dimension at the attribute level, and is also based on SQL/Temporal; we have not perceived a real SQL3 extension, but only how to simplify the expression of temporal predicates with the operators of the temporal logic. Indeed, the language considers that the operators used in this standard -as the cartesian product and the set operators of union, intersection and difference-does not influenced by the introduction of the temporal dimension.…”

Section: Related Workmentioning

confidence: 99%

Querying and Manipulating Temporal Databases

Mkaouar¹,

Bouaziz²,

Moalla³

2011

IJDMS

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“…Since the temporal data models use the term object loosely, one we may think of the possibility of integrating non-temporal database language such OODB or ORDB. With a non-temporal database language, it is a great burden for DB users to deal with temporal data all on their own [5]. For representing time varying data from the real world into objects, class diagram of the Unified Modeling Language (UML) has become a standard of the Information Technology.…”

Section: Introductionmentioning

confidence: 99%

Converting UML Class Diagrams into Temporal Object Relational DataBase

Soumiya

Bahaj

2017

IJECE

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Number of active researchers and experts, are engaged to develop and implement new mechanism and features in time varying database management system (TVDBMS), to respond to the recommendation of modern business environment.Time-varying data management has been much taken into consideration with either the attribute or tuple time stamping schema. Our main approach here is to try to offer a better solution to all mentioned limitations of existing works, in order to provide the nonprocedural data definitions, queries of temporal data as complete as possible technical conversion ,that allow to easily realize and share all conceptual details of the UML class specifications, from conception and design point of view. This paper contributes to represent a logical design schema by UML class diagrams, which are handled by stereotypes to express a temporal object relational database with attribute timestamping.

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A temporal object relational SQL language with attribute timestamping in a temporal transparency environment

Cited by 13 publications

References 27 publications

Temporal Data Update Methodologies for Data Warehousing

Temporal Data Update Methodologies for Data Warehousing

Querying and Manipulating Temporal Databases

Converting UML Class Diagrams into Temporal Object Relational DataBase

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